Edge AI: Revolutionizing Embedded Systems through On-Device Processing
DOI:
https://doi.org/10.32628/CSEIT251112289Keywords:
Artificial Intelligence, Edge Computing, Embedded Systems, Hardware Accelerators, Real-time ProcessingAbstract
This comprehensive article explores the transformative impact of edge AI computing on embedded systems, highlighting the paradigm shift from cloud-dependent to on-device processing. The article examines the architectural foundations, performance benefits, security advantages, and implementation considerations of edge AI systems. The article demonstrates how edge computing addresses critical challenges in latency, cost efficiency, data privacy, and operational reliability across various applications, particularly in autonomous systems. The article encompasses detailed analyses of hardware accelerators, memory architectures, power management strategies, and security frameworks, providing insights into both current capabilities and future developments. By examining real-world deployments across multiple sectors, the article illustrates how edge AI technology is revolutionizing embedded systems through improved processing efficiency, reduced operational costs, enhanced security measures, and optimized resource utilization.
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